AI Literacy Course


By : Khawar Nehal

khawar@atrc.net.pk

Date : 28 March 2025

Course Title: Understanding Artificial Intelligence – A Foundational Course
Duration: 4-6 Weeks (Flexible)
Level: Beginner to Intermediate

Module 1: Introduction to AI

Topics:

  • What is AI? (Definitions & Key Concepts)
  • History & Evolution of AI
  • Types of AI: Narrow AI vs. General AI vs. Superintelligence
  • Real-world Applications (Healthcare, Finance, Education, etc.)
  • Myths vs. Realities of AI

Activities:

  • Discussion: “Where do you encounter AI in daily life?”
  • Case Study: AI in a familiar industry (e.g., Netflix recommendations, Siri/Alexa)

Module 2: How AI Works – Core Concepts

Topics:

  • Machine Learning (ML) Basics
    • Supervised vs. Unsupervised vs. Reinforcement Learning
  • Neural Networks & Deep Learning (Simplified)
  • Natural Language Processing (NLP) & Computer Vision
  • Data’s Role in AI (Training, Testing, Bias)

Activities:

  • Interactive Demo: Play with a simple ML model (e.g., Google’s Teachable Machine)
  • Group Exercise: Identify AI vs. Non-AI systems

Module 3: Ethical & Societal Implications

Topics:

  • Bias & Fairness in AI
  • Privacy Concerns (Data Collection, Surveillance)
  • Job Disruption & Future of Work
  • AI in Misinformation (Deepfakes, ChatGPT-generated content)
  • Regulations & Responsible AI (EU AI Act, AI Ethics Principles)

Activities:

  • Debate: “Should AI decisions be transparent?”
  • Case Study: Facial recognition controversies

Module 4: AI in Everyday Life

Topics:

  • AI in Social Media (Algorithms, Content Moderation)
  • Smart Assistants (Siri, Alexa, Google Assistant)
  • AI in Healthcare (Diagnostics, Drug Discovery)
  • Autonomous Vehicles & Robotics
  • AI for Creativity (Art, Music, Writing)

Activities:

  • Hands-on: Use an AI tool (e.g., ChatGPT, DALL-E) for a task
  • Group Project: Propose an AI solution for a community problem

Module 5: Hands-On AI Exploration

Topics:

  • No-Code AI Tools (e.g., Lobe, Runway ML)
  • Prompt Engineering for Generative AI
  • How to Evaluate AI Tools Critically
  • Future Trends (Quantum AI, AGI, AI Safety)

Activities:

  • Lab: Create a simple AI chatbot or image classifier
  • Final Project: Present an AI use case (positive/negative impact)

Assessment & Certification

  • Quizzes per module
  • Participation in discussions/activities
  • Final project presentation
  • Optional: Badge/certificate of completion

Recommended Tools/Resources:

  • Google’s AI Experiments
  • Kaggle (for datasets)
  • OpenAI’s ChatGPT & DALL-E
  • IBM’s AI Ethics Toolkit


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